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Scaling modified condition/decision coverage using distributed concolic testing for Java programs

机译:使用针对Java程序的分布式condical测试扩展修改后的条件/决策覆盖

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Object-Oriented languages such as Java language introduce advantageous features which overcome the demerits of procedural languages to some extent. Therefore, Java language is now going to be used by the industries to develop their critical safety system software products. In this paper, we propose some code transformation methodologies, which are implemented in Java language to test Java written code. We apply Java Distributed Concolic testing technique to improve the code coverage, which is more powerful than non-distributed concolic testing in terms of speed of test case generation. We develop a Java coverage analyzer according to the test cases produced by Java distributed concolic testers. This version of the MC/DC analyzer is more powerful than that of procedural languages. Our core idea is to integrate the existing and developed modules to produce a single tool for measuring MC/DC score. This novel idea automates the flow of testing 100%. Our experimental results present different scenarios, and suggest the stronger one. On an average, for forty-five Java programs using three nodes in the client–server architecture, we achieved higher MC/DC score.
机译:诸如Java语言之类的面向对象的语言引入了有利的功能,这些功能在某种程度上克服了过程语言的缺点。因此,行业现在将使用Java语言来开发其关键安全系统软件产品。在本文中,我们提出了一些代码转换方法,这些方法以Java语言实现以测试Java编写的代码。我们使用Java Distributed Concolic测试技术来提高代码覆盖率,就测试用例的生成速度而言,它比非分布式conolicic测试更强大。我们根据Java分布式Condical测试人员产生的测试用例开发Java覆盖率分析器。此版本的MC / DC分析仪比过程语言更强大。我们的核心思想是整合现有和开发的模块,以产生一个用于测量MC / DC分数的工具。这个新颖的想法可以自动完成100%的测试流程。我们的实验结果提出了不同的方案,并提出了更强的方案。平均而言,对于使用客户机-服务器体系结构中三个节点的45个Java程序,我们获得了更高的MC / DC分数。

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